首页 | 本学科首页   官方微博 | 高级检索  
     检索      

非机动车跟驰模型的研究
引用本文:李星星,马健霄,徐佳逸.非机动车跟驰模型的研究[J].交通运输工程与信息学报,2012(1):115-120.
作者姓名:李星星  马健霄  徐佳逸
作者单位:南京林业大学,汽车与交通工程学院,南京210037
基金项目:江苏省自然科学基金项目(09KJD580005).
摘    要:交通仿真技术的广泛应用,提高了方案预测的准确性和实时再现性。在以模拟机动车为主的仿真软件不能较好满足国内混合交通的背景下,非机动车跟驰模型的研究尤为重要。论文首先参照机动车定义了非机动车的虚拟行车道,提出了跟驰状态的判断条件,以此作为非机动车跟驰行为的研究基础。其次,以车辆间应保持的最小安全车头间距为思路,充分考虑非机动车中电动自行车与自行车之间的差异,构建了非机动车的跟驰模型。最后,将模型所涉及的参数与宏观的交通流参数联系起来,通过流量、速度和密度关系,验证了模型的有效性。研究对于完善现有的交通仿真软件具有一定的参考和实用价值。

关 键 词:虚拟行车道  非机动车跟驰模型  安全车头间距  非机动车  交通仿真

Study on Non-motorized Vehicle-following Model
LI Xing-xing,MA Jian-xiao,XU Jia-yi.Study on Non-motorized Vehicle-following Model[J].Journal of Transportation Engineering and Information,2012(1):115-120.
Authors:LI Xing-xing  MA Jian-xiao  XU Jia-yi
Institution:(College of Automobile and Traffic Engineering, Nanjing Forestry University, Nanjing 210037, China)
Abstract:Traffic simulation is widely used to forecast and assess traffic engineering scenarios for it can improve the forecast accuracy and make scenarios visualization in real-time. Now, the foreign simulation softwares based on motor vehicle behaviors can not wellmatchthemixedtraffic of China, so research of anon-motorizedvehicle-followingmodel is particularly important. Firstly, this paper defined a virtual lane of a non-motorized vehicle by imitating the motor vehicle lane, and presented the condition to judge the following status of the non-motorized vehicle as a foundation for studying the non-motorized vehicle behavior in the following. Secondly, with the idea to maintain the minimum security headway, the paper estahlished a non-motorized vehicle-following model. Finally, combining the model parameters with the macroscopic traffic flow parameters, and according to the relationship among traffic flow, velocity and density, the paper certified and validated the above model.
Keywords:Virtual lane  non-motorized vehicle-following models  security headway  non-motorized vehicles  traffic simulation
本文献已被 CNKI 维普 等数据库收录!
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号